An evolutionary multiobjective approach for the dynamic multilevel component selection problem

Abstract

The architecture of a systems changes after the deployment phase due to new requirements thus the software architect must make decisions about the selection of the right software components out of a range of choices. This work deals with the component selection problem with a multilevel system view in an dynamic environment. We are approaching the problem as multiobjective using the Pareto dominance principle. The model aims to minimize the cost of the final solution while satisfying new requirements (or having available new components) keeping the complexity of the system as minimum as possible (in terms of used components). To validate our approach we performed experiments using a case study, a Reservation System application example. We have compared our approach with a random search algorithm using the Wilcoxon statistical test. The tests performed show the potential of evolutionary algorithms for the dynamic multilevel component selection problem.